Results 131 to 140 of about 2,020,572 (302)

Iron‐Mediated Release of Aged Dissolved Organic Carbon From Waterlogged Peatland Under Warming

Advanced Science, EarlyView.
This study conducts a five‐year in situ warming experiment in high‐altitude peatlands to examine dissolved organic carbon (DOC) release. The study shows that warming promotes the release of plant‐derived modern DOC in drained peatlands, but amplifies aquatic export of century‐old DOC from waterlogged peatlands via Fe‐mediated DOC mobilization—a ...
Guohua Dai, Zhiying Yang, Zongguang Liu, Wanjia Hu, Lixiao Ma, Enze Kang, Wanqing Luo, Yunpeng Zhao, Chengzhu Liu, Juan Jia, Ting Liu, Chen He, Quan Shi, Jianliang Liu, Yongheng Gao, Huai Chen, Hailong Zhang, Meixun Zhao, Xiaojuan Feng   +18 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

A general approach to Bayesian portfolio optimization [PDF]

We develop a general approach to portfolio optimization taking account of estimation risk and stylized facts of empirical finance. This is done within a Bayesian framework.
Bade, Alexander, Jaekel, Uwe, Frahm, Gabriel   +2 more
core  

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

Bayesian Estimation of a DSGE Model with Inventories [PDF]

This paper introduces inventories in an otherwise standard Dynamic Stochastic General Equilibrium Model (DSGE) of the business cycle. Firms accumulate inventories to facilitate sales, but face a cost of doing so in terms of costly storage of intermediate
Marcel Foerster
core  

Performance Quantile Regression and Bayesian Quantile Regression in Dealing with Non-normal Errors (Case Study on Simulated Data)

Numerical: Jurnal Matematika dan Pendidikan Matematika
This research discusses the performance of quantile regression and Bayesian quantile regression methods. Quantile regression uses parameter estimation by maximizing the value of the likelihood function, while Bayesian quantile regression uses parameter ...
Lilis Harianti Hasibuan, Ferra Yanuar, Vika Pradinda Harahap, Latifatul Qalbi   +3 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Structural Modeling of Marine Reserves with Bayesian Estimation [PDF]

Structural models can assess the effectiveness of fishery management prospectively and retrospectively. However, when only fishery-dependent data are available, structural econometric models are highly nonlinear in the parameters, and maximum likelihood ...
Coleman, Felicia C., Zhang, Junjie, Smith, Martin D.   +2 more
core  

Generation of Probabilistic Bits by Exploiting Orthogonal Spin Currents in Magnetic Trilayers

Advanced Science, EarlyView.
Fe/Ti/CoFeB trilayers generate orthogonal spin currents that drive stochastic spin–orbit‐torque switching for probabilistic‐bit operation. The switching probability is continuously controlled by the in‐plane magnetic field and drive current, enabling tunable random bit generation.
Donghyeon Han, Chaehyeon Shin, Seok‐Jong Kim, Yunho Jang, Daekyu Koh, Taehwan Kim, Jaeheon Jung, Geon‐Woo Baek, Minseok Kang, Eunseok Kim, Geun‐Hee Lee, Jeongchun Ryu, Makoto Kohda, Junsaku Nitta, Kab‐Jin Kim, Jongsun Park, Kyung‐Jin Lee, Byong‐Guk Park   +17 more
wiley   +1 more source

A Bayesian approach to parameter estimation for kernel density estimation via transformations [PDF]

In this paper, we present a Markov chain Monte Carlo (MCMC) simulation algorithm for estimating parameters in the kernel density estimation of bivariate insurance claim data via transformations.
David Pitt, Xueyuan Wu, Qing Liu, Xibin Zhang   +3 more
core